Measurement最新文献

{"title":"FID-Net: an interpretable fourier and image domain convolutional dictionary network for industrial CT metal artifact reduction","authors":"Xin Tian ,&nbsp;Zheng Yin ,&nbsp;Dalong Tan ,&nbsp;Yixin He ,&nbsp;Changzhe Li ,&nbsp;Tian Chen ,&nbsp;Yijie Peng ,&nbsp;Min Yang","doi":"10.1016/j.measurement.2026.121083","DOIUrl":"10.1016/j.measurement.2026.121083","url":null,"abstract":"<div><div>In battery X-ray computed tomography (CT) imaging, artifacts emanating from internal metallic implants markedly distort electrode morphology, thereby impeding precise interpretation and quantification of internal structural features. Although sinogram‑domain correction techniques can mitigate these artifacts to some extent, they frequently introduce secondary artifacts due to localized correction errors and entail substantial computational overhead. Meanwhile, most deep learning metal artifact reduction (MAR) methods treat the task as a generic image‑restoration problem, overlooking the inherent physics of CT imaging and relying solely on off‑the‑shelf network components, which limits their interpretability. To overcome these challenges, we propose FID‑Net, an interpretable Fourier and image domain convolutional dictionary network for industrial CT metal artifact reduction. FID‑Net constructs spatial and spectral dictionaries in parallel and uses the fast Fourier transform as an efficient bridge to jointly capture global context and local details, iteratively refining dictionary coefficients to accurately model and remove metal artifacts while fully preserving electrode morphology. To validate the effectiveness of the method, we constructed a real battery CT dataset and conducted comparative experiments on extensive synthetic and real data, and the results show that the proposed FID‑Net demonstrates superior performance in MAR effectiveness and structural fidelity.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121083"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large-range high-accuracy autocollimator using non-standard corner cube prism and multi-cross imaging","authors":"Xiaoyu Ma ,&nbsp;Long Ma ,&nbsp;Guifu Huang ,&nbsp;Igor Konyakhin ,&nbsp;Xinhai Zou ,&nbsp;Renpu Li ,&nbsp;Xiao Feng ,&nbsp;Junsen Yuan","doi":"10.1016/j.measurement.2026.121014","DOIUrl":"10.1016/j.measurement.2026.121014","url":null,"abstract":"<div><div>Investigating the mathematical relationship between the structure of a nonstandard corner cube prism and its reflection-angle sensitivity can guide the engineering design of large-range autocollimators. However, four measurement challenges are introduced: (1) degradation of measurement resolution; (2) redundant and confusing intersection points among multiple cross images; (3) reduced stability of pixel assignment within overlapping regions; and (4) ambiguity in fitting the imaging profile within pixel aggregation regions. This study overcomes these challenges by optimizing the utilization of the multidimensional reflective surfaces of a nonstandard corner cube prism to modulate the reflection-angle sensitivity of each cross-shaped imaging beam, in addition to designing a quadruple algorithm fusion recognition mechanism. Experimental results indicate that, whereas the measurement range of the autocollimator increases by a factor of 10, the mean measurement accuracy of the pitch and yaw angles reaches 0.41″ and 0.44″, respectively, within a 350″ range. Meanwhile, the mean measurement accuracy of the angles are less than 4.34″ and 4.62″, respectively, within an extended range of 10°.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121014"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SVMD-PE-SG for improved QEPAS-based methane concentration detection","authors":"Tingting Zhang,&nbsp;Yefeng Gu,&nbsp;Qinduan Zhang,&nbsp;Yubin Wei,&nbsp;Li Wang,&nbsp;Chunsheng Li,&nbsp;Wei Wang","doi":"10.1016/j.measurement.2026.120998","DOIUrl":"10.1016/j.measurement.2026.120998","url":null,"abstract":"<div><div>Methane (CH₄) has extensive applications in energy and chemical industries. However, its flammability and greenhouse effects necessitate timely detection of gas leakage for safety and environmental protection. This study presents a novel second harmonic signal denoising method for quartz-enhanced photoacoustic spectroscopy (QEPAS) CH₄ gas sensors. The proposed method integrates successive variational mode decomposition (SVMD), permutation entropy (PE), and Savitzky-Golay (SG) filtering. The methodology involves initial signal decomposition via SVMD, followed by PE threshold implementation to preserve effective signals during reconstruction, and subsequent SG filtering for enhanced denoising. In addition, we develop a parameter optimization approach to determine an appropriate balance parameter <span><math><mrow><mi>α</mi></mrow></math></span> for SVMD-based second harmonic signal decomposition. Both simulation and experimental results validate the superior performance of the SVMD-PE-SG method. The approach significantly improved the signal-to-noise ratio (SNR) from 54.58 to 298.49 and the correlation coefficient (R²) from 0.99682 to 0.99922, achieving a minimum detection limit (MDL) of 2.01 ppm for CH₄ gas. Through Allan variance analysis, the MDL reaches 67 ppb when the integration time is 121 s. Implementation of the SVMD-PE-SG algorithm substantially enhanced the detection accuracy of the CH₄-QEPAS gas sensor.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 120998"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive information fusion for multi-fault diagnosis using multi-stream convolutional neural network","authors":"R.K. Mishra ,&nbsp;Anurag Choudhary ,&nbsp;S. Fatima ,&nbsp;A.R. Mohanty ,&nbsp;B.K. Panigrahi","doi":"10.1016/j.measurement.2026.121043","DOIUrl":"10.1016/j.measurement.2026.121043","url":null,"abstract":"<div><div>The occurrence of multiple faults simultaneously in industrial machines is very complex. If maintenance operation is not carried out promptly, it leads to financial losses. Moreover, the unavailability of the multi-fault dataset imposes a problem for automated diagnosis model development. The model developed with a single sensor could not work with multiple sensor data and needs a separate fusion process. To tackle these problems, a robust methodology involving an Adaptive Information Fusion (AIF) process along with a Multi-Stream Convolutional Neural Network (MSCNN) is developed in this work. Initially, a large acoustics-based dataset is made by experimentally simulating 225 multi-fault conditions of motor, mechanical unbalance, system bearing and shaft misalignment at varying speeds. The acoustic signatures show distinct features with different fault conditions, passing through the AIF process for generating a time–frequency spectrum dataset using Wavelet Synchrosqueezed Transform (WSST). The spectrums are eventually used for training the optimised MSCNN model. A maximum overall classification accuracy of 97.19% is achieved. The performance of the methodology is rigorously tested under various background noise, data imbalance, speed conditions and with multi-sensor data fusion. The proposed method is useful for single as well as multiple-sensor data and can be helpful for incipient fault diagnosis in industries.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121043"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of a high-precision 3D measurement system via multi-source fusion and structural optimization of a Multi-Target Spatial Pose Determination Device (MSPD)","authors":"Han Wang ,&nbsp;Xuejian Zhang ,&nbsp;Zheyuan Zhang ,&nbsp;Xiaobing Hu ,&nbsp;Zhipeng Du","doi":"10.1016/j.measurement.2026.121050","DOIUrl":"10.1016/j.measurement.2026.121050","url":null,"abstract":"<div><div>To address the trade-off between measurement accuracy, field of view, and efficiency in large-scale dimensional metrology, this paper proposes a high-precision three-dimensional measurement method integrating a laser tracker and a binocular vision system. A Multi-Target Spatial Pose Determination Device (MSPD) is designed to establish a unified global reference frame and a stable pose linkage among heterogeneous measurement data, thereby reducing error accumulation and operational overhead in multi-station measurements. A multi-physics, multi-objective optimization model is formulated for the spatial layout of MSPD targets by incorporating geometric visibility, pose solvability, and structural constraints. The target configuration is optimized using a non-dominated sorting genetic algorithm (NSGA-II) to improve omnidirectional visibility and pose determination robustness. Experimental results show that the optimized MSPD achieves approximately 90% visibility coverage and maintains reliable target identification under varying observation poses. Calibration validation experiments yield a mean reprojection error of 0.1331 mm, confirming the accuracy and repeatability of the coordinate transformation and pose prediction models. Comparative multi-station experiments further demonstrate that, with only one initial calibration, the proposed MSPD-based tracking integration strategy achieves an average point position error of 0.3336 mm and a closed-loop consistency error of 0.2363 mm, while limiting additional operation time per station to 1–2 min. In contrast, station-by-station repeated calibration requires 15–20 min per station, and feature-based alignment exhibits significant error accumulation. These results indicate that the proposed fusion measurement framework provides an effective balance between accuracy, robustness, and operational efficiency, making it suitable for engineering-scale measurement of large and complex components and high-precision robotic calibration.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121050"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasensitive lead ion detection using polydopamine–maleic acid coated two-mode fiber with cascaded fiber Bragg grating compensation","authors":"Tengsheng Zhang ,&nbsp;Zixuan Liu ,&nbsp;Mengmeng Chen ,&nbsp;Namita Sahoo ,&nbsp;Kaiming Zhou ,&nbsp;Bing Sun ,&nbsp;Zuxing Zhang ,&nbsp;Xiankui Zeng ,&nbsp;Lin Zhang","doi":"10.1016/j.measurement.2026.120977","DOIUrl":"10.1016/j.measurement.2026.120977","url":null,"abstract":"<div><div>An ultrasensitive optical fiber sensor is developed for real-time and selective detection of lead (Pb²⁺) ions in aqueous environments. The device integrates a tapered two-mode fiber (<em>T</em>²MF) coated with a polydopamine–maleic acid (PDA–MA) film, which exhibits strong Pb²⁺ affinity through multidentate carboxyl coordination. The optimized taper geometry enables efficient excitation of the <span><math><mrow><mi>H</mi><msub><mrow><mi>E</mi></mrow><mrow><mtext>11</mtext></mrow></msub></mrow></math></span> and <span><math><mrow><mi>H</mi><msub><mrow><mi>E</mi></mrow><mrow><mtext>12</mtext></mrow></msub></mrow></math></span> modes, yeilding high refractive index sensitivity while retaining mechanical robustness. Upon Pb²⁺ binding, the local refractive index increases, including a redshift in the interference spectrum. Across concentrations from 2.07 to 207.2 ppb, the sensor demonstrates a linear spectral response (R²<span><math><mo>&gt;</mo></math></span>0.99) with a peak sensitivity of 0.219 nm/ppb and a detection limit of 2.4 ppb—well below the WHO drinking water standard. Incorporating a cascaded fiber Bragg grating (FBG) enables dual-parameter demodulation for real-time temperature compensation, ensuring high measurement fidelity. This compact and low-cost platform demonstrates strong selectivity, excellent reproducibility, and scalable potential for in situ heavy metal monitoring in environmental and public health applications.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 120977"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A study on coarse aggregate gradation detection based on shape factor estimation using GAT and Bayesian inference","authors":"Xiangyi Deng ,&nbsp;Yi Lu ,&nbsp;Ning Wang ,&nbsp;Lincheng Zhang","doi":"10.1016/j.measurement.2026.120980","DOIUrl":"10.1016/j.measurement.2026.120980","url":null,"abstract":"<div><div>The mass distribution of particles of different sizes is characterized by aggregate gradation, which is regarded as a key parameter determining mixture performance. Existing machine vision-based gradation detection methods exhibit considerable errors, mainly due to their excessive reliance on two-dimensional particle size features while neglecting particle morphological information. To address this issue, a novel method based on Graph Attention Networks (GAT) was proposed. Based on extracted aggregate size information, inferred particle shape factors were integrated to provide a more accurate representation of aggregate morphology. Dimensional features such as the equivalent Feret minor axis and the equivalent ellipse minor axis, together with multidimensional shape features including circularity and rectangularity, were first extracted. Subsequently, multi-temporal and multi-angle shape paradigms were constructed, through which the shape factors of aggregate particles were predicted by GAT. On this basis, an equivalent-sphere distribution theory was proposed, in which an aggregate set with unknown mass was transformed into a set of equivalent spheres with known mass, enabling the fusion of dimensional and morphological features. Finally, the gradation distribution was efficiently inferred by a Markov Chain Monte Carlo (MCMC) algorithm within a Bayesian statistical framework. Experimental results show that the absolute error of gradation detection is controlled within ± 3.0%. This represented a significant improvement over traditional size-feature-based methods and satisfied the ± 5% error tolerance required in engineering practice.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 120980"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of printing kinematics on dimensions, shape fidelity and GD&T parameters in 3D printing","authors":"Nagarjun Jayakumar,&nbsp;Balakrishnan Pandian","doi":"10.1016/j.measurement.2026.121015","DOIUrl":"10.1016/j.measurement.2026.121015","url":null,"abstract":"<div><div>3D printing has transformed manufacturing by enabling the rapid production of functional parts without the need for jigs, fixtures, or moulds. To fully exploit its potential in precision manufacturing, it is essential to evaluate the dimensional accuracy of different printing architectures. The present study compares the performance of Cartesian and Delta FDM printers in terms of dimensional accuracy, shape fidelity, and alignment precision. A novel geometric benchmark artefact was developed to evaluate GD&amp;T parameters and assess within-build repeatability across multiple features. Both printers were operated under identical process parameters and material conditions. Dimensional deviations between the printed parts and the CAD model were quantified using an optical 3D scanning technique. The results show that Cartesian printers achieve higher accuracy in planar and fine-detailed features, whereas Delta printers perform better for curved geometries. The Cartesian printer exhibited a mean negative deviation of −0.36 mm, while the Delta printer showed a mean positive deviation of +0.23 mm. Although the Delta printer demonstrated slightly lower overall error, it exhibited greater flatness deviations. These findings establish a systematic framework for precision evaluation in FDM and highlight the complementary strengths of Cartesian and Delta systems, providing guidance for printer selection based on application-specific requirements.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121015"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Logarithmic reordering kurtogram: An automatic resonance demodulation method for bearing fault diagnosis","authors":"Xin Zhang ,&nbsp;Xin Xiong ,&nbsp;Siqian Feng ,&nbsp;Jiaxu Wang ,&nbsp;Laihao Yang","doi":"10.1016/j.measurement.2026.120975","DOIUrl":"10.1016/j.measurement.2026.120975","url":null,"abstract":"<div><div>This paper proposes an automatic resonance demodulation method, the logarithmic reordering kurtogram (LRKurtogram), based on frequency band division and band evaluation for bearing fault diagnosis. Additional frequency band division is provided by the subband-reconstructed, rearranged, and ensemble dual-tree complex wavelet packet transform (SRRE-DTCWPT). Excellent performance of the dual-tree complex wavelet packet transform (DTCWPT) is thus achieved while mitigating the disorder problem in frequency subbands and band-leakage issues. Meanwhile, a robust band evaluation index based on the log-envelope, namely logarithmic reordering kurtosis, is designed to address the kurtosis index’s vulnerability to intense isolated impulse noise and its ineffectiveness. The effectiveness and improvements of the LRKurtogram are confirmed by analyzing several simulated and real signals and comparing with many advanced methods in the field. In particular, the LRKurtogram demonstrates remarkable effectiveness and robustness in extracting bearing fault characteristics from a series of signals with a wide range of signal-to-impulse noise ratios, highlighting its potential for bearing fault diagnosis.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120975"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full-field monitoring of segmental joint flexural tests using digital image correlation: a continuous non-contact methodology","authors":"Gong Yifan ,&nbsp;Ding Wenqi ,&nbsp;Jiang Hong ,&nbsp;Qiao Yafei","doi":"10.1016/j.measurement.2026.120946","DOIUrl":"10.1016/j.measurement.2026.120946","url":null,"abstract":"<div><div>With the continuous upscaling of tunnel cross-sections, the thickness of segmental linings shows progressive increasing. While increased thickness reduces overall structural failure risks, local joint damage remains a critical functional concern. However, conventional sensors struggle to capture detailed damage patterns due to their localized monitoring limitations. Digital Image Correlation (DIC) is a non-contact continuous monitoring technology and can easily realize the full-field monitoring. In this work, DIC is further developed to observe the joint deflection, joint rotational angle, crack width and damage distribution continuously. The proposed monitoring technology was applied in two flexural loading tests of segmental joints and validated by conventional sensors in the same set of test. The joint deflection and rotational angle measurements obtained from DIC agree well with those obtained from conventional displacement sensors under both positive and negative moment conditions. Additionally, the crack width measurement based on DIC offers a quantitative evaluation tool for monitoring the progression of joint damage. DIC measurements also revealed that the differences in joint design details could lead to distinct damage features under positive and negative bending moment conditions. Therefore, the utilization of DIC in joint loading tests overcomes certain limitations associated with conventional sensors and introduces new possibilities for research in this field.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120946"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}